Are Rising Tide students making progress toward our achievement accountability goal: “80% of Rising Students will test as at or above Benchmark in Reading on the Renaissance Star Reading and Star Mathematics screening assessments?
H1_null_Reading: There is no difference in the percentage of Rising Tide students classified as at or above benchmark in Reading in SY 2023-2024 and SY 2024-2025.
H1_alt_Reading: The percentage of Rising Tide students classified as at or above benchmark in Reading in SY 2023-2024 is less than the percentage of students classified as at or above benchmark in Reading in SY 2024-2025.
H1_null_Math: There is no difference in the percentage of Rising Tide students classified as at or above benchmark in Math in SY 2023-2024 and SY 2024-2025.
H1_alt_Math: The percentage of Rising Tide students classified as at or above benchmark in Math in SY 2023-2024 is less than the percentage of students classified as at or above benchmark in Math in SY 2024-2025.
Call:
lm(formula = `Test 1 PR` ~ School_Year_Fac + IEP_Status, data = star_dem_ELA)
Residuals:
Min 1Q Median 3Q Max
-58.281 -19.490 0.346 19.346 61.510
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 58.654 1.189 49.35 < 2e-16 ***
School_Year_Fac2024-2025 4.627 1.553 2.98 0.00296 **
IEP_Status1 -26.164 1.783 -14.67 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24.1 on 961 degrees of freedom
Multiple R-squared: 0.1884, Adjusted R-squared: 0.1868
F-statistic: 111.6 on 2 and 961 DF, p-value: < 2.2e-16
Code
AIC(fit_ELA_achieve)
[1] 8876.38
Code
BIC(fit_ELA_achieve)
[1] 8895.864
Visual: RQ1
Code
Bench_Sum_Plot<-HistSchoolBenchSum%>%filter(`Year`=="2024-2025"&`Screening Window`=="Winter"|`Year`=="2023-2024"&`Screening Window`=="Spring")%>%filter(`Benchmark_Status`=="At/Above Benchmark")%>%ggplot(aes(x=`Benchmark_Status`,fill =`Year`, y =`% Students`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`% Students`, label =`% Students`,vjust =-.25), position =position_dodge(width =1)) +#theme_classic() +theme(axis.title.x=element_blank(),# axis.text.x = element_text(angle = 45, , hjust = 1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+labs(y ="% Students",x="Benchmark Category",title ="Rising Tide Benchmark Achievement by School Year",caption ="Source: Renaissance Star Literacy and Math Screening")+geom_hline(yintercept =80, color ="grey")+#annotate("text", x = .75, y = 85, label = "80% Goal")# +facet_wrap(~Subject)
Code
#| eval: false#| fig-cap: "Rising Tide Benchmark Achievement by School Year, Renaissance Star Literacy and Math"#| fig-alt: >#| A bar blot with school year (ordered, factor) on the x-axis and the percentage of students#| classified as At/Above benchmark on the y-axis, faceted by subject (English Language Arts or Math)#| Plot illustrates the relationship between the three variables.Bench_Sum_Plot
Subject Level Fall Winter Growth Comparison
ELA Growth
Code
Growth_Sum_ELA<-star_dem_all_private%>%filter(`School_Year`=="2024-2025")%>%filter(`Assignment Type`=="Star Reading")%>%group_by(Grade)%>%summarize(median_SGP=median(`SGP (Expectation=50)`))Growth_Sum_ELA_Plot<-ggplot(Growth_Sum_ELA, aes(x=`Grade`, y =`median_SGP`,fill="skyblue")) +geom_bar(position="dodge", stat ="identity", fill="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`median_SGP`, label =`median_SGP`,vjust =-.25))+theme_classic()+#scale_color_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Literacy Student Growth Percentile by Grade Level",caption ="Source: 2024-2025 Renaissance Star Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =1., y =52, label ="50th Percentile")
Code
Growth_Sum_ELA_Plot
ELA Historical Growth
Code
Hist_Growth_Sum_ELA_Plot<-HistGradeGrowthSum%>%filter(Subject =="ELA")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Grade`,fill ="skyblue", y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", fill ="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`,vjust =-.25), position =position_dodge(width =1))+#theme_classic()+#scale_fill_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Literacy Student Growth Percentile by Grade Level",caption ="Source: Renaissance Star Literacy Screening")+geom_hline(yintercept =50, color ="grey")+#annotate("text", x = 1.55, y = 52, label = "50th Percentile")+facet_wrap(~Year)
Code
Hist_Growth_Sum_ELA_Plot
Rising Tide Literacy Growth by Grade Level, school year 2024-2025 and 2023-2024, Renaissance Star Literacy Screening
Math Growth
Code
Growth_Sum_Math<-star_dem_all_private%>%filter(`Assignment Type`=="Star Math")%>%filter(`School_Year`=="2024-2025")%>%group_by(Grade)%>%summarize(median_SGP=median(`SGP (Expectation=50)`))Growth_Sum_Math_Plot<-ggplot(Growth_Sum_Math, aes(x=`Grade`,fill =`Grade`, y =`median_SGP`, fill="skyblue")) +geom_bar(position="dodge", stat ="identity", fill="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`median_SGP`, label =`median_SGP`,vjust =-.25))+theme_classic()+scale_fill_brewer(palette ="Blues")+theme(axis.title.x=element_blank(),axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Math Student Growth Percentile by Grade Level",caption ="Source: 2024-2025 Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =1.05, y =53, label ="50th Percentile")
Code
Growth_Sum_Math_Plot
Code
Hist_Growth_Sum_Math_Plot<-HistGradeGrowthSum%>%filter(Subject =="Math")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Grade`,fill ="skyblue", y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", fill ="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`,vjust =-.25), position =position_dodge(width =1))+#theme_classic()+#scale_fill_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Math Student Growth Percentile by Grade Level",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =5.5, y =48, label ="50th Percentile")+facet_wrap(~Year)
Code
Hist_Growth_Sum_Math_Plot
Rising Tide Math Growth by Grade Level, school year 2024-2025 and 2023-2024, Renaissance Star Math Screening
RQ2 Grade 5 Math
Is there a relationship between Rising Tide’s Grade 5 Mathematics curriculum initiatives and Grade 5 student growth in mathematics?
H2_null: There is no difference in the student growth percentile (SGP) for Grade 5 students in SY 2023-2024 and SY 2024-2025
H2_alt: The student growth percentile (SGP) for Grade 5 students in SY 2023-2024 is less than the student growth percentile (SGP) for Grade 5 students in SY 2024-2025.
Hist_Growth_Sum_G5Math_Plot<-HistGradeGrowthSum%>%filter(Subject =="Math")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Grade`,fill =ifelse(Grade =="5", "A", "B"), y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", show.legend=FALSE) +scale_fill_manual(values =c(A="skyblue", B ="grey"))+#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`,vjust =-.25), position =position_dodge(width =1))+#theme_classic()+#scale_fill_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Math Student Growth Percentile by Grade Level",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+#annotate("text", x = 5.5, y = 48, label = "50th Percentile")+facet_wrap(~Year)
Code
Hist_Growth_Sum_G5Math_Plot
Rising Tide Math Growth by Grade Level, school year 2024-2025 and 2023-2024, Renaissance Star Math Screening
Code
Hist_Growth_G5Math_Plot<-HistGradeGrowthSum%>%filter(Subject =="Math")%>%filter(Grade =="5")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Year`,fill ="skyblue", y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", fill ="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`, vjust =-.25), position =position_dodge(width =1))+theme_classic()+scale_fill_brewer(palette ="Paired")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="School Year",title ="Improvement in Grade 5 Student Growth Percentile",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =1., y =52, label ="Goal 50th Percentile")#+#theme_classic()#facet_wrap(~Year)
Code
Hist_Growth_G5Math_Plot
Rising Tide Grade 5 Math Growth by school year 2024-2025 and 2023-2024, Renaissance Star Math Screening
Visual G5 IEP Growth
Code
IEP_Growth_G5Math_Plot<- Math_IEP_Sum%>%filter(Grade =="5")%>%ggplot(aes(x=`IEP`,fill =`School_Year`, y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Median SGP`, x =`IEP`, label =`Median SGP`), position =position_dodge(width=.9),vjust =1)+theme_classic()+theme(#axis.title.x=element_blank(),#axis.text.x=element_blank(),# axis.text.x=element_text(angle =45, hjust = 1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+# facet_wrap(~`Screening Window`)+labs(y ="Median SGP",x="IEP Status",title ="Improved Growth For All Grade 5 Learners",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =.70, y =52, label ="50th Percentile")#+
Code
IEP_Growth_G5Math_Plot
Rising Tide Grade 5 Math Growth by disability status (IEP) and school year 2024-2025 and 2023-2024, Renaissance Star Math Screening
RQ 3: ELA State Standards Mastery
Is there a relationship between the text type of a literacy standard (informational vs. literature) and Rising Tide High School students’ mastery of the standard?
H3_null: There is no difference between Rising Tide High School students’ mean mastery score for literature reading standards and their mean mastery score for informational text reading standards.
H3_alt: Rising Tide High School students’ mean mastery score for literature reading standards is higher than their mean mastery score for informational text reading standards.
HS_ELA_Text_Facet <- HS_ELA_Standards %>%ggplot( aes(x=`% Secure`, fill=`Text Type`)) +geom_histogram( color="#e9ecef", alpha=0.6,binwidth=15, position ='identity') +scale_fill_manual(values=c("#69b3a2", "#404080")) +theme_classic() +labs( y ="",title ="High School State Standard Mastery Distribution",x ="% Students Secure",caption ="Star Reading: State Standards Mastery")+facet_wrap(~`Text Type`)HS_ELA_Text_Facet
Statistical Tests
Code
fit_ELA_text =lm(`% Secure`~ ( `Text Type`+`Screening Window`+`Domain`), data = ELA_Standards)summary(fit_ELA_text)
Call:
lm(formula = `% Secure` ~ (`Text Type` + `Screening Window` +
Domain), data = ELA_Standards)
Residuals:
Min 1Q Median 3Q Max
-40.934 -8.667 2.097 8.740 34.360
Coefficients:
Estimate Std. Error t value
(Intercept) 47.593 1.932 24.631
`Text Type`Literature 4.294 1.707 2.515
`Screening Window`Winter 6.658 1.698 3.920
DomainIntegration of Knowledge and Ideas 4.310 2.248 1.917
DomainKey Ideas and Details 2.458 2.137 1.150
DomainRange of Reading and Level of Text Complexity -4.611 3.022 -1.526
Pr(>|t|)
(Intercept) < 2e-16 ***
`Text Type`Literature 0.012609 *
`Screening Window`Winter 0.000118 ***
DomainIntegration of Knowledge and Ideas 0.056484 .
DomainKey Ideas and Details 0.251263
DomainRange of Reading and Level of Text Complexity 0.128519
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 12.82 on 222 degrees of freedom
(309 observations deleted due to missingness)
Multiple R-squared: 0.121, Adjusted R-squared: 0.1012
F-statistic: 6.11 on 5 and 222 DF, p-value: 2.523e-05
Code
fit_HS_ELA_text_domain =lm(`% Secure`~ ( `Text Type`+`Screening Window`+`Domain`), data = HS_ELA_Standards)summary(fit_HS_ELA_text_domain)
Call:
lm(formula = `% Secure` ~ (`Text Type` + `Screening Window` +
Domain), data = HS_ELA_Standards)
Residuals:
Min 1Q Median 3Q Max
-28.378 -8.155 -1.182 7.971 40.030
Coefficients:
Estimate Std. Error t value
(Intercept) 39.314 3.175 12.382
`Text Type`Literature 8.840 2.806 3.151
`Screening Window`Winter 4.947 2.791 1.773
DomainIntegration of Knowledge and Ideas 7.276 3.694 1.970
DomainKey Ideas and Details 1.708 3.512 0.486
DomainRange of Reading and Level of Text Complexity 3.417 4.967 0.688
Pr(>|t|)
(Intercept) <2e-16 ***
`Text Type`Literature 0.0024 **
`Screening Window`Winter 0.0806 .
DomainIntegration of Knowledge and Ideas 0.0528 .
DomainKey Ideas and Details 0.6282
DomainRange of Reading and Level of Text Complexity 0.4938
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 12.17 on 70 degrees of freedom
(38 observations deleted due to missingness)
Multiple R-squared: 0.1886, Adjusted R-squared: 0.1307
F-statistic: 3.255 on 5 and 70 DF, p-value: 0.01063
Code
AIC(fit_HS_ELA_text_domain)
[1] 603.2177
Code
BIC(fit_HS_ELA_text_domain)
[1] 619.5328
Code
stargazer(fit_ELA_text, type ="text")
===============================================================================
Dependent variable:
---------------------------
`% Secure`
-------------------------------------------------------------------------------
`Text Type`Literature 4.294**
(1.707)
`Screening Window`Winter 6.658***
(1.698)
DomainIntegration of Knowledge and Ideas 4.310*
(2.248)
DomainKey Ideas and Details 2.458
(2.137)
DomainRange of Reading and Level of Text Complexity -4.611
(3.022)
Constant 47.593***
(1.932)
-------------------------------------------------------------------------------
Observations 228
R2 0.121
Adjusted R2 0.101
Residual Std. Error 12.823 (df = 222)
F Statistic 6.110*** (df = 5; 222)
===============================================================================
Note: *p<0.1; **p<0.05; ***p<0.01
Code
stargazer(fit_HS_ELA_text_domain, type ="text")
===============================================================================
Dependent variable:
---------------------------
`% Secure`
-------------------------------------------------------------------------------
`Text Type`Literature 8.840***
(2.806)
`Screening Window`Winter 4.947*
(2.791)
DomainIntegration of Knowledge and Ideas 7.276*
(3.694)
DomainKey Ideas and Details 1.708
(3.512)
DomainRange of Reading and Level of Text Complexity 3.417
(4.967)
Constant 39.314***
(3.175)
-------------------------------------------------------------------------------
Observations 76
R2 0.189
Adjusted R2 0.131
Residual Std. Error 12.166 (df = 70)
F Statistic 3.255** (df = 5; 70)
===============================================================================
Note: *p<0.1; **p<0.05; ***p<0.01
Visual Mastery by Text Type
Schoolwide
Code
#ELA_StandardsELA_Text_Summary<-ELA_Standards%>%filter(`Reporting Category`=="Reading")%>%group_by(`Text Type`, `Screening Window`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`)),`Median % Secure`=round(median(`% Secure`)))#ELA_Text_SummaryELA_Text_Summary%>%filter(`Screening Window`!="Spring")%>%ggplot(aes(x=`Text Type`,fill =`Text Type`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Mean % Secure`, x =`Text Type`, label =`Mean % Secure`), position =position_dodge(width=.9),vjust =1)+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.text.x=element_text(angle =45, hjust =1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+facet_wrap(~`Screening Window`)+labs(y ="Mean % Secure",x="Domainl",title ="School State Standard Mastery by Text Type ELA",caption ="Source: 2024-2025 Renaissance Star Reading Screening")
ELA_Text_Div_Summary%>%filter(`Screening Window`!="Spring")%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Mean % Secure`, x =`Text Type`, label =`Mean % Secure`), position =position_dodge(width=.9),vjust =1)+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.text.x=element_text(angle =45, hjust =1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+facet_wrap(~`Division`)+labs(y ="Mean % Secure",x="Domainl",title ="School State Standard Mastery by Text Type ELA",caption ="Source: 2024-2025 Renaissance Star Reading Screening")
By Domain Cluster
Code
ELA_Text_Domain_Summary%>%filter(`Screening Window`!="Spring")%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Mean % Secure`, x =`Text Type`, label =`Mean % Secure`), position =position_dodge(width=.9),vjust =1)+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.text.x=element_text(angle =45, hjust =1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+facet_wrap(~`Domain`)+labs(y ="Mean % Secure",x="Domain",title ="School State Standard Mastery by Text Type ELA",caption ="Source: 2024-2025 Renaissance Star Reading Screening")
Visual: HS Informational Text vs. Literature Comparison
Code
ELA_Standards
Code
ELA_TextType_Sum_HS<-ELA_Standards%>%filter(`Division`=="HS")%>%filter (`Screening Window`!="Spring")%>%filter(`Reporting Category`=="Reading")%>%group_by(`Screening Window`, Grade, `Text Type`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`))) ELA_TextType_Sum_HS%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +#scale_x_reverse()+geom_text(aes( y =`Mean % Secure`, label =`Mean % Secure`,vjust =-.25), position =position_dodge(width =1)) +#theme_classic() +theme(axis.title.x=element_blank(),# axis.text.x=element_blank(),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+labs(y ="Mean % Secure",x="Text Type",title ="HS Reading Standards Mastery by Text Type",caption ="Source: 2024-2025 Renaissance Star Reading Screening")+facet_wrap(~Grade)
Visual: MS Informational Text vs. Literature Mastery: Fall-Winter
Code
ELA_TextType_Sum_MS<-ELA_Standards%>%filter(`Division`=="MS")%>%filter (`Screening Window`!="Spring")%>%filter(`Reporting Category`=="Reading")%>%group_by(`Screening Window`, Grade, `Text Type`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`))) ELA_TextType_Sum_MS%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +#scale_x_reverse()+geom_text(aes( y =`Mean % Secure`, label =`Mean % Secure`,vjust =-.25), position =position_dodge(width =1)) +#theme_classic() +theme(axis.title.x=element_blank(),# axis.text.x=element_blank(),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+labs(y ="Mean % Secure",x="Text Type",title ="MS Reading Standards Mastery by Text Type",caption ="Source: 2024-2025 Renaissance Star Reading Screening")+facet_wrap(~Grade)
Code
#ELA_Standards
Source Code
---title: "DACSS 604 Final Project"author: "Theresa Szczepanski"format: html: df-print: paged toc: true code-fold: true code-copy: true code-tools: true embed-resources: true self-contained-math: trueeditor: markdown: wrap: 72---# Load Libraries```{r}#| label: setup#| warning: false#| message: false# load the needed librarieslibrary(tidyverse)library(ggplot2)library(lubridate)library(readxl)library(hrbrthemes)library(viridis)library(ggpubr)library(purrr)library(plotly)library(dplyr)library(RColorBrewer)library(stargazer)knitr::opts_chunk$set(echo =TRUE, warning=FALSE, message=FALSE)#source('readin_lib.R')#source('student_perf_lib.R')```# Load the Data## State Standards Mastery Summary```{r}ELA_Standards<-read_csv("data_604/State_Standards-_Mastery_Star_2425_ELA.csv")%>%mutate(Division =case_when( Grade ==9| Grade ==10~"HS", Grade ==5| Grade ==6| Grade ==7| Grade ==8~"MS" ))%>%mutate(Grade =as.factor(Grade))%>%mutate(`Reporting Category`=as.factor(`Reporting Category`))%>%mutate(`Domain`=as.factor(`Domain`))%>%mutate(`Division`=as.factor(`Division`))%>%mutate(`Screening Window`=as.factor(`Screening Window`))%>%mutate(`Text Type`=as.factor(`Text Type`))ELA_Standards```## Growth/Demographic Summary```{r}star_dem_all_private<-read_csv("data_604/student_star_dem_all_private.csv")%>%mutate(`Grade`=as.factor(`Grade`))%>%mutate(`Grade`=recode_factor(`Grade`,"5"="5","6"="6","7"="7","8"="8","9"="9","10"="10",.ordered =TRUE))%>%mutate(School_Year =as.factor(School_Year))%>%mutate(School_Year_Fac = School_Year)%>%mutate(School_Year =recode_factor(School_Year,"2023-2024"="2023-2024","2024-2025"="2024-2025",.ordered =TRUE))%>%mutate(`Assignment Type`=as.factor(`Assignment Type`))%>%mutate(`Test 1 Benchmark Category`=recode_factor(`Test 1 Benchmark Category`,"At/Above Benchmark"="At/Above Benchmark","On Watch"="On Watch","Intervention"="Intervention","Urgent Intervention"="Urgent Intervention",.ordered =TRUE))%>%mutate(IEP_Status =as.factor(IEP_Status))%>%mutate(`504_Status`=as.factor(`504_Status`))%>%mutate(`Low_Income_Status`=as.factor(Low_Income_Status))%>%mutate(`Gender`=as.factor(Gender) )%>%mutate(`Gender_Status`=case_when( Gender =="Male"~0, Gender =="Female"~1 ))star_dem_all_private```## Historical Summary Data Frames```{r}HistSchoolBenchSum<-read_csv("data_604/StarBenchmarkSummary_School.csv")%>%mutate(Year =as.factor(Year))%>%mutate(`Screening Window`=as.factor(`Screening Window`))%>%mutate(`Benchmark_Status`=recode_factor(`Benchmark_Status`,"At/Above Benchmark"="At/Above Benchmark","Below Benchmark"="Below Benchmark",.ordered =TRUE))%>%select(Year, `Screening Window`, Subject, `Benchmark_Status`, `% Students`)HistSchoolBenchSumHistGradeGrowthSum<-read_csv("data_604/StarBenchmarkSummary_SGP_Sum.csv")%>%mutate(Year =as.factor(Year))%>%mutate(`Screening Window`=as.factor(`Screening Window`))%>%mutate(`Subject`=as.factor(`Subject`))%>%mutate(`Grade_Fac`=as.factor(Grade))%>%mutate(`Grade`=as.factor(Grade))%>%mutate(`Grade`=recode_factor(`Grade`,"Grade 5"="Grade 5","Grade 6"="Grade 6","Grade 7"="Grade 7","Grade 8"="Grade 8","Grade 9"="Grade 9","Grade 10"="Grade 10",.ordered =TRUE))%>%select(Year, `Screening Window`, `Grade`, Subject, `Median SGP`)HistGradeGrowthSum```# RQ1:Are Rising Tide students making progress toward our achievementaccountability goal: “80% of Rising Students will test as at or aboveBenchmark in Reading on the Renaissance Star Reading and StarMathematics screening assessments?## Historical Benchmark_Status```{r}star_dem_all_private<-star_dem_all_private%>%mutate(Benchmark_Status =case_when(`Test 1 PR`>=40~"At/Above Benchmark",`Test 1 PR`<40~"Below Benchmark"))%>%mutate(Benchmark_Status =as.factor(Benchmark_Status))```### Statistical Test- **H1_null_Reading**: There is no difference in the percentage of Rising Tide students classified as at or above benchmark in Reading in SY 2023-2024 and SY 2024-2025.- **H1_alt_Reading**: The percentage of Rising Tide students classified as at or above benchmark in Reading in SY 2023-2024 is less than the percentage of students classified as at or above benchmark in Reading in SY 2024-2025.- **H1_null_Math**: There is no difference in the percentage of Rising Tide students classified as at or above benchmark in Math in SY 2023-2024 and SY 2024-2025.- **H1_alt_Math**: The percentage of Rising Tide students classified as at or above benchmark in Math in SY 2023-2024 is less than the percentage of students classified as at or above benchmark in Math in SY 2024-2025.#### Achievement: Math```{r}star_dem_math<- star_dem_all_private%>%filter(`Assignment Type`=="Star Math")star_dem_mathfit_Math_achieve =lm(`Test 1 PR`~ School_Year_Fac +`IEP_Status`+`504_Status`+`Low_Income_Status`, data = star_dem_math)summary(fit_Math_achieve)AIC(fit_Math_achieve)BIC(fit_Math_achieve)#star_dem_mathstar_dem_math```#### Achievement: ELA```{r}star_dem_ELA<- star_dem_all_private%>%filter(`Assignment Type`=="Star Reading")fit_ELA_achieve =lm(`Test 1 PR`~ School_Year_Fac +`IEP_Status`, data = star_dem_ELA)summary(fit_ELA_achieve)AIC(fit_ELA_achieve)BIC(fit_ELA_achieve)```### Visual: RQ1```{r}Bench_Sum_Plot<-HistSchoolBenchSum%>%filter(`Year`=="2024-2025"&`Screening Window`=="Winter"|`Year`=="2023-2024"&`Screening Window`=="Spring")%>%filter(`Benchmark_Status`=="At/Above Benchmark")%>%ggplot(aes(x=`Benchmark_Status`,fill =`Year`, y =`% Students`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`% Students`, label =`% Students`,vjust =-.25), position =position_dodge(width =1)) +#theme_classic() +theme(axis.title.x=element_blank(),# axis.text.x = element_text(angle = 45, , hjust = 1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+labs(y ="% Students",x="Benchmark Category",title ="Rising Tide Benchmark Achievement by School Year",caption ="Source: Renaissance Star Literacy and Math Screening")+geom_hline(yintercept =80, color ="grey")+#annotate("text", x = .75, y = 85, label = "80% Goal")# +facet_wrap(~Subject)``````{r}#| eval: false#| fig-cap: "Rising Tide Benchmark Achievement by School Year, Renaissance Star Literacy and Math"#| fig-alt: >#| A bar blot with school year (ordered, factor) on the x-axis and the percentage of students#| classified as At/Above benchmark on the y-axis, faceted by subject (English Language Arts or Math)#| Plot illustrates the relationship between the three variables.Bench_Sum_Plot```# Subject Level Fall Winter Growth Comparison## ELA Growth```{r}Growth_Sum_ELA<-star_dem_all_private%>%filter(`School_Year`=="2024-2025")%>%filter(`Assignment Type`=="Star Reading")%>%group_by(Grade)%>%summarize(median_SGP=median(`SGP (Expectation=50)`))Growth_Sum_ELA_Plot<-ggplot(Growth_Sum_ELA, aes(x=`Grade`, y =`median_SGP`,fill="skyblue")) +geom_bar(position="dodge", stat ="identity", fill="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`median_SGP`, label =`median_SGP`,vjust =-.25))+theme_classic()+#scale_color_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Literacy Student Growth Percentile by Grade Level",caption ="Source: 2024-2025 Renaissance Star Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =1., y =52, label ="50th Percentile")``````{r}#| eval: false#| fig-cap: "Rising Tide Literacy Growth by Grade Level, 2024-2025 Renaissance Star Literacy Screening"#| fig-alt: >#| A bar blot with Grade level (ordered, factor) on the x-axis and the median student growth percentile #| (SGP) in literacy on the y-axis#| Plot illustrates the relationship between the two variables.Growth_Sum_ELA_Plot```### ELA Historical Growth```{r}Hist_Growth_Sum_ELA_Plot<-HistGradeGrowthSum%>%filter(Subject =="ELA")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Grade`,fill ="skyblue", y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", fill ="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`,vjust =-.25), position =position_dodge(width =1))+#theme_classic()+#scale_fill_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Literacy Student Growth Percentile by Grade Level",caption ="Source: Renaissance Star Literacy Screening")+geom_hline(yintercept =50, color ="grey")+#annotate("text", x = 1.55, y = 52, label = "50th Percentile")+facet_wrap(~Year)``````{r}#| eval: true#| fig-cap: "Rising Tide Literacy Growth by Grade Level, school year 2024-2025 and 2023-2024, Renaissance Star Literacy Screening"#| #| fig-alt: >#| A bar blot with Grade level (ordered, factor) on the x-axis and the median student growth percentile #| (SGP) in literacy on the y-axis, faceted by school year (ordered, factor).#| Plot illustrates the relationship between the three variables.#| Hist_Growth_Sum_ELA_Plot```## Math Growth```{r}Growth_Sum_Math<-star_dem_all_private%>%filter(`Assignment Type`=="Star Math")%>%filter(`School_Year`=="2024-2025")%>%group_by(Grade)%>%summarize(median_SGP=median(`SGP (Expectation=50)`))Growth_Sum_Math_Plot<-ggplot(Growth_Sum_Math, aes(x=`Grade`,fill =`Grade`, y =`median_SGP`, fill="skyblue")) +geom_bar(position="dodge", stat ="identity", fill="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`median_SGP`, label =`median_SGP`,vjust =-.25))+theme_classic()+scale_fill_brewer(palette ="Blues")+theme(axis.title.x=element_blank(),axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Math Student Growth Percentile by Grade Level",caption ="Source: 2024-2025 Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =1.05, y =53, label ="50th Percentile")``````{r}#| eval: false#| fig-cap: "Rising Tide Math Growth by Grade Level, 2024-2025 Renaissance Star Literacy Screening"#| fig-alt: >#| A bar blot with Grade level (ordered, factor) on the x-axis and the median student growth percentile #| (SGP) in math on the y-axis#| Plot illustrates the relationship between the two variables.Growth_Sum_Math_Plot``````{r}Hist_Growth_Sum_Math_Plot<-HistGradeGrowthSum%>%filter(Subject =="Math")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Grade`,fill ="skyblue", y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", fill ="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`,vjust =-.25), position =position_dodge(width =1))+#theme_classic()+#scale_fill_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Math Student Growth Percentile by Grade Level",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =5.5, y =48, label ="50th Percentile")+facet_wrap(~Year)``````{r}#| eval: true#| fig-cap: "Rising Tide Math Growth by Grade Level, school year 2024-2025 and 2023-2024, Renaissance Star Math Screening"#| #| fig-alt: >#| A bar blot with Grade level (ordered, factor) on the x-axis and the median student growth percentile #| (SGP) in math on the y-axis, faceted by school year (ordered, factor).#| Plot illustrates the relationship between the three variables.#| Hist_Growth_Sum_Math_Plot```# RQ2 Grade 5 MathIs there a relationship between Rising Tide’s Grade 5 Mathematicscurriculum initiatives and Grade 5 student growth in mathematics?**H2_null:** There is no difference in the student growth percentile(SGP) for Grade 5 students in SY 2023-2024 and SY 2024-2025**H2_alt:** The student growth percentile (SGP) for Grade 5 students inSY 2023-2024 is less than the student growth percentile (SGP) for Grade5 students in SY 2024-2025.## Summary Data Frames```{r}Math_IEP_Sum<-star_dem_math%>%mutate(IEP =case_when(IEP_Status ==1~"Yes", IEP_Status ==0~"No"))%>%filter(`Assignment Type`=="Star Math")%>%group_by(Grade, `School_Year`, IEP)%>%summarize(`Median SGP`=median(`SGP (Expectation=50)`))```## Visual: Growth Distribution```{r}MathHistGrowth<- star_dem_mathG5MathHistGrowth<-star_dem_math%>%filter(Grade =="5")G5_Hist_Year <- G5MathHistGrowth %>%ggplot( aes(x=`SGP (Expectation=50)`, fill=School_Year)) +geom_histogram( color="#e9ecef", alpha=0.6,binwidth=10, position ='identity') +scale_fill_manual(values=c("#69b3a2", "#404080")) +theme_classic() +labs(fill="")#+# facet_wrap(~Year)G5_Hist_YearG5_Hist_Year_Facet <- G5MathHistGrowth %>%ggplot( aes(x=`SGP (Expectation=50)`, fill=School_Year)) +geom_histogram( color="#e9ecef", alpha=0.6,binwidth=15, position ='identity') +scale_fill_manual(values=c("#69b3a2", "#404080")) +theme_classic() +labs(fill="")+labs( y ="",title ="Grade 5 Student Growth Distribution",x ="Student Growth Percentile (SGP)",caption ="Star Math Assessments")+facet_wrap(~School_Year)G5_Hist_Year_FacetGrowth_Hist<-MathHistGrowth%>%ggplot( aes(x=`SGP (Expectation=50)`)) +#geom_histogram(alpha=0.6, binwidth = 15) +#ggplot(aes()+geom_histogram(alpha = .9, binwidth =15)+#scale_fill_viridis(discrete=TRUE) +#scale_color_viridis(discrete=TRUE) +theme_classic()#Growth_Hist```## Statistical Tests```{r}#summary(MathHistGrowth)G5MathHistGrowth<-G5MathHistGrowth%>%mutate(School_Year_Factor =case_when( School_Year =="2023-2024"~"2023-2024", School_Year =="2024-2025"~"2024-2025"))%>%mutate(School_Year_Factor =as.factor(School_Year_Factor))%>%mutate(School_Year_Bool =case_when(`School_Year`=="2023-2024"~0,`School_Year`=="2024-2025"~1 ))fit_G5Math_growth_dem =lm(`SGP (Expectation=50)`~ School_Year_Factor +`IEP_Status`+`Low_Income_Status`+`504_Status`+`Test 1 PR`, data = G5MathHistGrowth)summary(fit_G5Math_growth_dem)AIC(fit_G5Math_growth_dem)BIC(fit_G5Math_growth_dem)``````{r}stargazer(fit_G5Math_growth_dem, type ="text") ```### Diagnosing Model Fit```{r}plot(fit_G5Math_growth_dem, which =1:6)cooks=4/179cooks #.0223```## Visual G5 Math Growth```{r}Hist_Growth_Sum_G5Math_Plot<-HistGradeGrowthSum%>%filter(Subject =="Math")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Grade`,fill =ifelse(Grade =="5", "A", "B"), y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", show.legend=FALSE) +scale_fill_manual(values =c(A="skyblue", B ="grey"))+#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`,vjust =-.25), position =position_dodge(width =1))+#theme_classic()+#scale_fill_brewer(palette = "Blues")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="Grade Level",title ="Math Student Growth Percentile by Grade Level",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+#annotate("text", x = 5.5, y = 48, label = "50th Percentile")+facet_wrap(~Year)``````{r}#| eval: true#| fig-cap: "Rising Tide Math Growth by Grade Level, school year 2024-2025 and 2023-2024, Renaissance Star Math Screening"#| #| fig-alt: >#| A bar blot with Grade level (ordered, factor) on the x-axis and the median student growth percentile #| (SGP) in math on the y-axis, faceted by school year (ordered, factor).#| Plot illustrates the relationship between the three variables.#| Hist_Growth_Sum_G5Math_Plot``````{r}Hist_Growth_G5Math_Plot<-HistGradeGrowthSum%>%filter(Subject =="Math")%>%filter(Grade =="5")%>%filter(`Screening Window`=="Fall-Winter")%>%ggplot(aes(x=`Year`,fill ="skyblue", y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity", fill ="skyblue") +#facet_wrap(~Grade)+geom_text(aes( y =`Median SGP`, label =`Median SGP`, vjust =-.25), position =position_dodge(width =1))+theme_classic()+scale_fill_brewer(palette ="Paired")+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.ticks.x=element_blank())+labs(y ="Median SGP",x="School Year",title ="Improvement in Grade 5 Student Growth Percentile",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =1., y =52, label ="Goal 50th Percentile")#+#theme_classic()#facet_wrap(~Year)``````{r}#| eval: true#| fig-cap: "Rising Tide Grade 5 Math Growth by school year 2024-2025 and 2023-2024, Renaissance Star Math Screening"#| #| fig-alt: >#| A bar blot with school year (ordered, factor) on the x-axis and the median G5 student growth #| percentile (SGP) in math on the y-axis.#| Plot illustrates the relationship between the two variables.#| Hist_Growth_G5Math_Plot```## Visual G5 IEP Growth```{r} IEP_Growth_G5Math_Plot<- Math_IEP_Sum%>%filter(Grade =="5")%>%ggplot(aes(x=`IEP`,fill =`School_Year`, y =`Median SGP`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Median SGP`, x =`IEP`, label =`Median SGP`), position =position_dodge(width=.9),vjust =1)+theme_classic()+theme(#axis.title.x=element_blank(),#axis.text.x=element_blank(),# axis.text.x=element_text(angle =45, hjust = 1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+# facet_wrap(~`Screening Window`)+labs(y ="Median SGP",x="IEP Status",title ="Improved Growth For All Grade 5 Learners",caption ="Source: Renaissance Star Math Screening")+geom_hline(yintercept =50, color ="grey")+annotate("text", x =.70, y =52, label ="50th Percentile")#+``````{r}#| eval: true#| fig-cap: "Rising Tide Grade 5 Math Growth by disability status (IEP) and school year 2024-2025 and 2023-2024, Renaissance Star Math Screening"#| #| fig-alt: >#| A clustered, bar blot with IEP status (ordered, factor) on the x-axis and the #| median G5 student growthpercentile (SGP) in math on the y-axis.#| Bars are colored by the school year (ordered, factor)#| Plot illustrates the relationship between the three variables.#| IEP_Growth_G5Math_Plot```# RQ 3: ELA State Standards MasteryIs there a relationship between the text type of a literacy standard(informational vs. literature) and Rising Tide High School students’mastery of the standard?**H3_null:** There is no difference between Rising Tide High Schoolstudents’ mean mastery score for literature reading standards and theirmean mastery score for informational text reading standards.**H3_alt:** Rising Tide High School students’ mean mastery score forliterature reading standards is higher than their mean mastery score forinformational text reading standards.## Visual: Distribution ELA Standards Mastery```{r}HS_ELA_Standards<-ELA_Standards%>%filter(Grade ==9|Grade ==10)%>%filter(`Text Type`=="Informational Text"|`Text Type`=="Literature")HS_ELA_StandardsHS_ELA_Text_Facet <- HS_ELA_Standards %>%ggplot( aes(x=`% Secure`, fill=`Text Type`)) +geom_histogram( color="#e9ecef", alpha=0.6,binwidth=15, position ='identity') +scale_fill_manual(values=c("#69b3a2", "#404080")) +theme_classic() +labs( y ="",title ="High School State Standard Mastery Distribution",x ="% Students Secure",caption ="Star Reading: State Standards Mastery")+facet_wrap(~`Text Type`)HS_ELA_Text_Facet```## Statistical Tests```{r}fit_ELA_text =lm(`% Secure`~ ( `Text Type`+`Screening Window`+`Domain`), data = ELA_Standards)summary(fit_ELA_text)fit_HS_ELA_text_domain =lm(`% Secure`~ ( `Text Type`+`Screening Window`+`Domain`), data = HS_ELA_Standards)summary(fit_HS_ELA_text_domain)AIC(fit_HS_ELA_text_domain)BIC(fit_HS_ELA_text_domain)``````{r}stargazer(fit_ELA_text, type ="text")stargazer(fit_HS_ELA_text_domain, type ="text")```## Visual Mastery by Text Type### Schoolwide```{r}#ELA_StandardsELA_Text_Summary<-ELA_Standards%>%filter(`Reporting Category`=="Reading")%>%group_by(`Text Type`, `Screening Window`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`)),`Median % Secure`=round(median(`% Secure`)))#ELA_Text_SummaryELA_Text_Summary%>%filter(`Screening Window`!="Spring")%>%ggplot(aes(x=`Text Type`,fill =`Text Type`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Mean % Secure`, x =`Text Type`, label =`Mean % Secure`), position =position_dodge(width=.9),vjust =1)+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.text.x=element_text(angle =45, hjust =1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+facet_wrap(~`Screening Window`)+labs(y ="Mean % Secure",x="Domainl",title ="School State Standard Mastery by Text Type ELA",caption ="Source: 2024-2025 Renaissance Star Reading Screening")ELA_Text_Domain_Summary<-ELA_Standards%>%filter(`Reporting Category`=="Reading")%>%group_by(`Text Type`, `Domain`, `Screening Window`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`)),`Median % Secure`=round(median(`% Secure`)))#ELA_Text_Domain_SummaryELA_Text_Div_Summary<-ELA_Standards%>%filter(`Reporting Category`=="Reading")%>%group_by(`Text Type`, `Division`, `Screening Window`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`)),`Median % Secure`=round(median(`% Secure`)))#ELA_Text_Div_Summary```### MS vs. HS```{r}ELA_Text_Div_Summary%>%filter(`Screening Window`!="Spring")%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Mean % Secure`, x =`Text Type`, label =`Mean % Secure`), position =position_dodge(width=.9),vjust =1)+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.text.x=element_text(angle =45, hjust =1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+facet_wrap(~`Division`)+labs(y ="Mean % Secure",x="Domainl",title ="School State Standard Mastery by Text Type ELA",caption ="Source: 2024-2025 Renaissance Star Reading Screening")```### By Domain Cluster```{r}ELA_Text_Domain_Summary%>%filter(`Screening Window`!="Spring")%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +geom_text(aes( y =`Mean % Secure`, x =`Text Type`, label =`Mean % Secure`), position =position_dodge(width=.9),vjust =1)+theme(axis.title.x=element_blank(),#axis.text.x=element_blank(),axis.text.x=element_text(angle =45, hjust =1),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+facet_wrap(~`Domain`)+labs(y ="Mean % Secure",x="Domain",title ="School State Standard Mastery by Text Type ELA",caption ="Source: 2024-2025 Renaissance Star Reading Screening")```## Visual: HS Informational Text vs. Literature Comparison```{r}ELA_StandardsELA_TextType_Sum_HS<-ELA_Standards%>%filter(`Division`=="HS")%>%filter (`Screening Window`!="Spring")%>%filter(`Reporting Category`=="Reading")%>%group_by(`Screening Window`, Grade, `Text Type`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`))) ELA_TextType_Sum_HS%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +#scale_x_reverse()+geom_text(aes( y =`Mean % Secure`, label =`Mean % Secure`,vjust =-.25), position =position_dodge(width =1)) +#theme_classic() +theme(axis.title.x=element_blank(),# axis.text.x=element_blank(),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+labs(y ="Mean % Secure",x="Text Type",title ="HS Reading Standards Mastery by Text Type",caption ="Source: 2024-2025 Renaissance Star Reading Screening")+facet_wrap(~Grade)```## Visual: MS Informational Text vs. Literature Mastery: Fall-Winter```{r}ELA_TextType_Sum_MS<-ELA_Standards%>%filter(`Division`=="MS")%>%filter (`Screening Window`!="Spring")%>%filter(`Reporting Category`=="Reading")%>%group_by(`Screening Window`, Grade, `Text Type`)%>%summarize(`Mean % Secure`=round(mean(`% Secure`))) ELA_TextType_Sum_MS%>%ggplot(aes(x=`Text Type`,fill =`Screening Window`, y =`Mean % Secure`)) +geom_bar(position="dodge", stat ="identity") +#scale_x_reverse()+geom_text(aes( y =`Mean % Secure`, label =`Mean % Secure`,vjust =-.25), position =position_dodge(width =1)) +#theme_classic() +theme(axis.title.x=element_blank(),# axis.text.x=element_blank(),axis.ticks.x=element_blank())+scale_fill_brewer(palette ="Paired")+labs(y ="Mean % Secure",x="Text Type",title ="MS Reading Standards Mastery by Text Type",caption ="Source: 2024-2025 Renaissance Star Reading Screening")+facet_wrap(~Grade)#ELA_Standards```